Dopamine transporter (DAT) imaging in Parkinson’s disease and related disorders

2021 ◽  
Author(s):  
Thomas Brücke ◽  
Christof Brücke
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dopamine Transporter

scholarly journals Using Artificial Neural Network to Discriminate Parkinson’s Disease from Other Parkinsonisms by Focusing on Putamen of Dopamine Transporter SPECT Images

Biomedicines ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 12
Author(s):  
Chung-Yao Chien ◽  
Szu-Wei Hsu ◽  
Tsung-Lin Lee ◽  
Pi-Shan Sung ◽  
Chou-Ching Lin
Keyword(s):  
Neural Network ◽  
Parkinson’S Disease ◽  
Artificial Neural Network ◽  
Support Vector Machine ◽  
Parkinson's Disease ◽  
Dopamine Transporter ◽  
Support Vector ◽  
Dat Spect ◽  
Ann Classifier ◽  
Spect Images

Background: The challenge of differentiating, at an early stage, Parkinson’s disease from parkinsonism caused by other disorders remains unsolved. We proposed using an artificial neural network (ANN) to process images of dopamine transporter single-photon emission computed tomography (DAT-SPECT). Methods: Abnormal DAT-SPECT images of subjects with Parkinson’s disease and parkinsonism caused by other disorders were divided into training and test sets. Striatal regions of the images were segmented by using an active contour model and were used as the data to perform transfer learning on a pre-trained ANN to discriminate Parkinson’s disease from parkinsonism caused by other disorders. A support vector machine trained using parameters of semi-quantitative measurements including specific binding ratio and asymmetry index was used for comparison. Results: The predictive accuracy of the ANN classifier (86%) was higher than that of the support vector machine classifier (68%). The sensitivity and specificity of the ANN classifier in predicting Parkinson’s disease were 81.8% and 88.6%, respectively. Conclusions: The ANN classifier outperformed classical biomarkers in differentiating Parkinson’s disease from parkinsonism caused by other disorders. This classifier can be readily included into standalone computer software for clinical application.

scholarly journals Refining diagnosis of Parkinson's disease with deep learning-based interpretation of dopamine transporter imaging

2017 ◽  
Vol 16 ◽  
pp. 586-594 ◽  
Author(s):  
Hongyoon Choi ◽  
Seunggyun Ha ◽  
Hyung Jun Im ◽  
Sun Ha Paek ◽  
Dong Soo Lee
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Dopamine Transporter ◽  
Dopamine Transporter Imaging

P.5.d.005 Reduced dopamine transporter binding predates impulse control disorders in Parkinson's disease

2013 ◽  
Vol 23 ◽  
pp. S548-S549
Author(s):  
O.A. Van den Heuvel ◽  
C. Vriend ◽  
A.H. Nordbeck ◽  
J. Booij ◽  
Y.D. Van der Werf ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dopamine Transporter ◽  
Impulse Control ◽  
Impulse Control Disorders

scholarly journals Asymmetric Dopamine Transporter Loss Affects Cognitive and Motor Progression in Parkinson's Disease

2021 ◽  
Author(s):  
Eleonora Fiorenzato ◽  
Angelo Antonini ◽  
Patrizia Bisiacchi ◽  
Luca Weis ◽  
Roberta Biundo
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dopamine Transporter

Increased dopamine transporter density in Parkinson's disease patients with social anxiety disorder

2011 ◽  
Vol 310 (1-2) ◽  
pp. 53-57 ◽  
Author(s):  
Tais S. Moriyama ◽  
André C. Felicio ◽  
Marcos H.N. Chagas ◽  
Vítor S. Tardelli ◽  
Henrique Ballalai Ferraz ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Anxiety Disorder ◽  
Social Anxiety ◽  
Dopamine Transporter ◽  
Social Anxiety Disorder
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